Instructions to use Helsinki-NLP/opus-mt-es-ar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-es-ar with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-es-ar")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-es-ar") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-es-ar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e08e490be72a853843d8b7d3c3b2c140b04ca325afeb0b9794e4a5520afe225
- Size of remote file:
- 307 MB
- SHA256:
- 7a7e25757653fd3975f75afe47ddc30990fe44f1cd6945b1db86c3cf3cca13d5
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